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Innovative Final-Year Undergraduate Design Project Course Using an International Project

2006· article· en· W2122568573 on OpenAlexafffundabout
Janaka Y. Ruwanpura, Thomas G. Brown

Bibliographic record

VenueJournal of Professional Issues in Engineering Education and Practice · 2006
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversity of Calgary
FundersUniversity of Calgary
KeywordsEngineeringCapstoneEngineering managementComponent (thermodynamics)Engineering design processProcess (computing)Project managementEngineering educationEngineering ethicsProject-based learningMulticulturalismCivil engineeringSystems engineeringPedagogySociologyComputer scienceMechanical engineering

Abstract

fetched live from OpenAlex

This paper describes the organization and conduct of a 4th year capstone project for civil engineering students at the University of Calgary that embodied a very significant international component and the difficulties inherent to that component. The project design education process results in numerous contributions to university, industry, and society by permitting students to develop innovative design solutions that reflect multicultural influences, while also recognizing that Civil Engineering design is universal. This paper explains the novel approach adopted for the final-year civil engineering design course in 2002–2003 using the largest urban renewal project currently underway in Europe, for which the students had the opportunity to develop designs. The concept, structure, challenges, and contributions as well as the successful outcome of the civil engineering design course are also explained in the paper. Overall, this design project provided the students with valuable experience in communication, design, professional practice, and organizational skills that will be useful in their future careers, in addition to the challenges of dealing with a real and international client of a complex project.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score0.652

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.043
GPT teacher head0.390
Teacher spread0.347 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2006
Admission routes3
Has abstractyes

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